【摘 要】
:
可再生能源、电动汽车大量接入使得对配电网的实时状态估计难度提高。现有的配电网量测系统难以满足对含有大量不确定性的分布式电源和电动汽车的配电系统的态势感知要求。为此,本文提出一种面向区间状态估计的配电系统同步相量测量单元优化配置方法。基于各节点与其他节点的最小路径,构建最小区间状态估计平均区间宽度目标的数学模型,以最大冗余度和最小区间状态估计平均区间宽度为目标函数,以配置数量为约束,建立多目标的优化配置模型。采用基于精英策略的非支配性排序遗传算法(NSGA-Ⅱ)求取模型的最优解集。通过NSGA-Ⅱ求解多次所
【机 构】
:
广东电网有限责任公司广州供电局,广东工业大学自动化学院
【基金项目】
:
广东电网有限责任公司广州供电局科技项目(GZHKJXM 20190062)。
论文部分内容阅读
可再生能源、电动汽车大量接入使得对配电网的实时状态估计难度提高。现有的配电网量测系统难以满足对含有大量不确定性的分布式电源和电动汽车的配电系统的态势感知要求。为此,本文提出一种面向区间状态估计的配电系统同步相量测量单元优化配置方法。基于各节点与其他节点的最小路径,构建最小区间状态估计平均区间宽度目标的数学模型,以最大冗余度和最小区间状态估计平均区间宽度为目标函数,以配置数量为约束,建立多目标的优化配置模型。采用基于精英策略的非支配性排序遗传算法(NSGA-Ⅱ)求取模型的最优解集。通过NSGA-Ⅱ求解多次所
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